You can use the COVB(DETAILS) option to diagnose the adjustments that PROC GLIMMIX makes to the covariance matrix of fixed-effects parameter estimates.Īn application with DDFM=KENWARDROGER is presented in Example 41.8. Of the DDFM=KENWARDROGER option eliminates the second derivatives from the calculation of the covariance matrix adjustment.įor scalar estimable functions, the resulting estimator is referred to as the Prasad-Rao estimator in Harville and Jeske ( 1992). Also, the resultingĪdjusted covariance matrix can then be indefinite and is not invariant under reparameterization. This term can result in standard error shrinkage. For covariance structures that have nonzero second derivatives with respect to the covariance parameters, the Kenward-RogerĬovariance matrix adjustment includes a second-order term. This bias-adjusted precision estimator is also discussed in Prasad and Rao ( 1990) Harville and Jeske ( 1992) Kackar and Harville ( 1984).īy default, the observed information matrix of the covariance parameter estimates is used in the calculations. ![]() This method uses to address the fact that is a biased estimator of, and itself underestimates when is unknown. The precision estimator is bias-adjusted, in contrast to the conventional precision estimator, which is obtained by simply replacing with in, the asymptotic variance of. The value of m thus derived is the Kenward-Roger degrees of freedom. An appropriate approximation to the sampling distribution of is derived by matching the first two moments of with those from the approximating F distribution and solving for the values of and m. ![]() Where, is a bias-adjusted estimator of the precision of, and.
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